# battery soc estimation using EKF

조회 수: 8 (최근 30일)
Rihane boutaina . 2021년 4월 2일
답변: Sabin . 2023년 9월 22일
hello,
please i need help ! i'm trying to estimate the battery state of charge using kalman filtering ! but actually i have no clue :/
i've written this programme but it doesnt work ?!
any one can help me please ! i'm feeling really stuck :(
clc
tic
% Enter input data
i=tryfilekalmanS1(:,3);
vt=tryfilekalmanS1(:,2);
soc=tryfilekalmanS5(:,1);
t=tryfilekalman(:,1);
OCV=tryfilekalmanS2(:,2);
OCV=table2array(OCV);
current=table2array(i);
voltage=table2array(vt);
SOC=table2array(soc);
Time=table2array(t);
%battery parameters
Cn=2.6; %battery nominal capacity
deltat=5; %time step
R=0.1174; %internal resistance
taud=4.4925;
eff=1; %coulomb effeiciency (for discharging case it takes 1)
sigmaW =30; %process noise covariance
sigmaV=20; %sensor noise covariance
F=(-2.6/taud);A=-2.6;B=1;C=0.1;D=1; %plant definition matrices
maxIter=16; %number of iterations to execute simulation
% Providing the value of battery parameters (ocv(soc) curve fitting
% equation)
M0=277512.69155; % Coefficient from OCV fitting curve
M1=-110959.5326; % Coefficient from OCV fitting curve
M2=14761.90214; % Coefficient from OCV fitting curve
M3=-653.33323; % Coefficient from OCV fitting curve
I = current;
V=voltage;
for k=1:maxIter
%initialization
xtrue(1)=1; %initialise true system initial state
xhat(1)=0; %initialise kalman filter initial estimate
sigmaX(1)=0.005; %initialise kalman filter covariance
u=7.7783; %unknown initial driving input
%time update
xhat=A*(M0 + M1.*OCV(k) + M2.*OCV(k)^2+ M3.*OCV(k)^3)+w;
sigmaX=A*sigmaX*A'+sigmaW;
%
u=OCV;
w=0.012; v=0.023; %noises
ytrue = C.*xhat+D.*u+v;
xtrue = A*xtrue+B*u+w;
%Estimate system output
yhat=C*xhat+D*u;
%Compute kalman gain matrix
sigmaY=C*sigmaX*C'+sigmaV;
L=sigmaX*C'/sigmaY;
%measurement update
xhat=xhat+L*(ytrue-yhat);
sigmaX=sigmaX-L*sigmaY*L';
%store
xstore(1:16,k)= xtrue(1:16);
xhatstore(1:16,k)=xhat(1:16);
sigmaXstore(1:1,k)=sigmaX(1:1);
ytruestore(1:17,k)=ytrue(1:17);
yhatstore(1:17,k)=yhat(1:17);
end
toc
%code plot
figure(1);
plot(1:maxIter,xstore(1:maxIter)','r',1:maxIter,xhatstore',1:maxIter,xhatstore(1:maxIter)-xstore(1:maxIter)','b');
grid;
legend('true','estimate','error');
title('soc estimation');
xlabel('time'); ylabel('soc');

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### 답변 (1개)

Sabin 2023년 9월 22일
Simscape Battery is a useful place to start with battery modeling and BMS functionality.
An example of SOC estimation:
I hope this helps.

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